Sata Busayarat

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A method for modelling and visualizing human lungs using knowledge of lung anatomy and high resolution CT (HRCT) images is presented. The model consists of a symbolic description of lung anatomy and a 3D atlas. The 3D atlas is constructed using HRCT volume data. A few anatomical landmarks are determined and are used to divide the lungs into anatomically and(More)
A method for modelling human lungs is presented. The model includes both knowledge of lung anatomy and knowledge of the appearance of objects in high resolutions CT images of the lungs. Symbolic, structural and geometric information in the model is stored in frame structures. Frames allow easy representation of the hierarchical structures that are found in(More)
Bronchial dilatation is one of the most important direct signs for the diagnosis of bronchiectasis in high-resolution CT images of the lung. The assessment of the dilatation is done by comparing the size of the bronchus and accompanying artery. Previous work has shown that the success of an automatic bronchial dilatation detection method is limited by high(More)
Image registration is a fundamental problem in medical imaging. It is especially challenging in lung images compared, for example, with the brain. The challenges include large anatomical variations of human lung and a lack of fixed landmarks inside the lung. This paper presents a new method for lung HRCT image registration. It employs a landmark-based(More)
The identification of bronchi on High-resolution CT (HRCT) images of the lung provides valuable clinical information in patients with suspected airways diseases such as bronchiectasis. This paper presents a new method for automatic detection of bronchi for sparse HRCT data. Using sparse instead of volumetric data helps reduce the amount of data needed to be(More)